Introduction Adrenal myelolipoma (AML) is the second most common, and invariably benign primary adrenal neoplasm. Due to the variable proportion of fat and hematopoietic elements, and its often large size, it can cause differential diagnostic problems. Several reports confirmed the utility of microRNAs (miRNAs) in the diagnosis of tumors, but the miRNA expression in AML has not yet been investigated. Materials and methods Next-generation sequencing (NGS) was performed on 30 formalin-fixed paraffin-embedded (FFPE) archived tissue [AML, adrenocortical adenoma (ACA) and adrenocortical carcinoma (ACC) 10 each] samples. Validation was performed by real-time RT-qPCR on a cohort containing 41 further FFPE samples (15 AML, 14 ACA and 12 ACC). Circulating miRNA counterparts of significantly differentially expressed tissue miRNAs were studied in altogether 33 plasma samples (ACA, ACC, AML 11 each). Results By NGS, 256 significantly differentially expressed miRNAs were discovered, and 8 of these were chosen for validation. Significant overexpression of hsa-miR-451a, hsa-miR-486-5p, hsa-miR-363-3p and hsa-miR-150-5p was confirmed in AML relative to ACA and ACC. Hsa-miR-184, hsa-miR-483-5p and hsa-miR-183-5p were significantly overexpressed in ACC relative to ACA, but not to AML. Circulating hsa-miR-451a and hsa-miR-363-3p were significantly overexpressed in AML, whereas circulating hsa-miR-483-5p and hsa-miR-483-3p were only significantly overexpressed in ACC vs. ACA. Conclusions We have found significantly differentially expressed miRNAs in AML and adrenocortical tumors. Circulating hsa-miR-451a might be a promising minimally invasive biomarker of AML. The lack of significantly different expression of hsa-miR-483-3p and hsa-miR-483-5p between AML and ACC might limit their applicability as diagnostic miRNA markers for ACC.

The histological analysis of adrenal tumors is difficult and requires great expertise. Tissue microRNA (miRNA) expression is distinct between benign and malignant tumors of several organs and can be useful for diagnostic purposes. MiRNAs are stable and their expression can be reliably reproduced from archived formalin-fixed, paraffin-embedded (FFPE) tissue blocks. Our purpose was to assess the potential applicability of combinations of literature-based miRNAs as markers of adrenocortical malignancy. Archived FFPE tissue samples from 10 adrenocortical carcinoma (ACC), 10 adrenocortical adenoma (ACA) and 10 normal adrenal cortex samples were analyzed in a discovery cohort, while 21 ACC and 22 ACA patients were studied in a blind manner in the validation cohort. The expression of miRNA was determined by RT-qPCR. Machine learning and neural network-based methods were used to find the best performing miRNA combination models. To evaluate diagnostic applicability, ROC-analysis was performed. We have identified three miRNA combinations (hsa-miR-195 + hsa-miR-210 + hsa-miR-503; hsa-miR-210 + hsa-miR-375 + hsa-miR-503 and hsa-miR-210 + hsa-miR-483-5p + hsa-miR-503) as unexpectedly good predictors to determine adrenocortical malignancy with sensitivity and specificity both of over 90%. These miRNA panels can supplement the histological examination of removed tumors and could even be performed from small volume adrenal biopsy samples preoperatively.

Almost 10 years have passed since the first attempts of liquid biopsy aimed at the characterisation of tumor cells present in the bloodstream from a regular sample of peripheral blood were performed. Liquid biopsy has been used to characterise tumor heterogeneity in various types of solid tumors including adrenocortical carcinoma. The development of molecular biology, genetics, and methodological advances such as digital PCR and next-generation sequencing allowed us to use besides circulating tumor cells a variety of circulating cell-free nucleic acids, DNAs, RNAs and microRNAs secreted by tumors into blood and other body fluids as specific molecular markers. These markers are used for diagnosis, to check tumor development, selecting efficient therapies, therapy monitoring and even possess prognostic power. In adrenocortical carcinoma, there are some studies reporting analysis of circulating tumor cells, circulating cell free DNA and microRNAs for assessing tumor heterogeneity. Among microRNAs, hsa-miR-483-5p seems to be the most important player. Combined with other microRNAs like hsa-miR-195, their expression correlates with recurrence-free survival. Most studies support the applicability of liquid biopsy for assessing temporal tumor heterogeneity (i.e. tumor progression) in adrenocortical cancer. In this mini-review, the available findings of liquid biopsy for assessing tumor heterogeneity in adrenocortical cancer are presented.

Quantitative PCR (qPCR) is used for the determination of gene copy number (GCN). GCNs contribute to human disorders, and characterize copy number variation (CNV). The single laboratory method validations of duplex qPCR assays with hydrolysis probes on CYP21A1P and CYP21A2 genes, residing a CNV (RCCX CNV) and related to congenital adrenal hyperplasia, were performed using 46 human genomic DNA samples. We also performed the verifications on 5 qPCR assays for the genetic elements of RCCX CNV; C4A, C4B, CNV breakpoint, HERV-K(C4) CNV deletion and insertion alleles. Precision of each qPCR assay was under 1.01 CV%. Accuracy (relative error) ranged from 4.96±4.08% to 9.91±8.93%. Accuracy was not tightly linked to precision, but was significantly correlated with the efficiency of normalization using the RPPH1 internal reference gene (Spearman’s ρ: 0.793–0.940, p>0.0001), ambiguity (ρ = 0.671, p = 0.029) and misclassification (ρ = 0.769, p = 0.009). A strong genomic matrix effect was observed, and target-singleplex (one target gene in one assay) qPCR was able to appropriately differentiate 2 GCN from 3 GCN at best. The analysis of all GCNs from the 7 qPCR assays using a multiplex approach increased the resolution of differentiation, and produced 98% of GCNs unambiguously, and all of which were in 100% concordance with GCNs measured by Southern blot, MLPA and aCGH. We conclude that the use of an internal (in one assay with the target gene) reference gene, the use of allele-specific primers or probes, and the multiplex approach (in one assay or different assays) are crucial for GCN determination using qPCR or other methods.

Pancreatic neuroendocrine neoplasms pose a growing clinical challenge due to their rising incidence and variable prognosis. The current study aims to investigate microRNAs (miRNA; miR) as potential biomarkers for distinguishing between grade 1 (G1) and grade 2 (G2) pancreatic neuroendocrine tumors (PanNET). A total of 33 formalin-fixed, paraffin-embedded samples were analyzed, comprising 17 G1 and 16 G2 tumors. Initially, literature-based miRNAs were validated via real-time quantitative reverse transcription polymerase chain reaction (RT-qPCR), confirming significant downregulation of miR-130b-3p and miR-106b in G2 samples. Through next-generation sequencing, we have identified and selected the top six miRNAs showing the highest difference between G1 and G2 tumors, which were further validated. RT-qPCR validation confirmed the downregulation of miR-30d-5p in G2 tumors. miRNA combinations were created to distinguish between the two PanNET grades. The highest diagnostic performance in distinguishing between G1 and G2 PanNETs by a machine learning algorithm was achieved when using the combination miR-106b + miR-130b-3p + miR-127-3p + miR-129-5p + miR-30d-5p. The ROC analysis resulted in a sensitivity of 83.33% and a specificity of 87.5%. The findings underscore the potential use of miRNAs as biomarkers for stratifying PanNET grades, though further research is warranted to enhance diagnostic accuracy and clinical utility.

Differentiation of adrenocortical adenoma (ACA) and carcinoma (ACC) is often challenging even in the histological analysis. Circular RNAs (circRNAs) belonging to the group of non-coding RNAs have been implicated as relevant factors in tumorigenesis. Our aim was to explore circRNA expression profiles in adrenocortical tumors by next-generation sequencing followed by RT-qPCR validation. Archived FFPE (formalin-fixed, paraffin embedded) including 8 ACC, 8 ACA and 8 normal adrenal cortices (NAC) were used in the discovery cohort. For de novo and known circRNA expression profiling, a next-generation sequencing platform was used. CIRI2, CircExplorer2, AutoCirc bioinformatics tools were used for the discovery of circRNAs. The top five most differentially circRNAs were measured by RT-qPCR in an independent validation cohort (10 ACC, 8 ACA, 8 NAC). In silico predicted, interacting microRNAs potentially sponged by differentially expressed circRNAs were studied by individual RT-qPCR assays. We focused on overexpressed circRNAs here. Significantly differentially expressed circRNAs have been revealed between the cohorts by NGS. Only circPHC3 could be confirmed to be significantly overexpressed in ACC, ACA vs. NAC samples by RT-qPCR. We could not observe microRNA expression changes fully corresponding to our sponging hypothesis. To the best of our knowledge, our study is the first to investigate circRNAs in adrenocortical tumors. Further studies are warranted to explore their biological and diagnostic relevance.